package com.atguigu.gmall.realtime.app.dwm;

import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONObject;
import com.atguigu.gmall.realtime.utils.MyKafkaUtil;
import org.apache.flink.api.common.functions.RichFilterFunction;
import org.apache.flink.api.common.state.StateTtlConfig;
import org.apache.flink.api.common.state.ValueState;
import org.apache.flink.api.common.state.ValueStateDescriptor;
import org.apache.flink.api.common.time.Time;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;

import java.text.SimpleDateFormat;

/**
 * Author: Felix
 * Date: 2021/11/6
 * Desc: 独立访客计算
 * 需要启动进程
 *      zk、kafka、logger.sh(nginx、日志采集服务)、[hdfs]、BaseLogApp、UniqueVisitorApp
 * 执行流程
 *      >模拟生成日志数据
 *      >nginx进行负载均衡
 *      >日志采集服务对日志进行处理      发送到kafka的ods_base_log
 *      >BaseLogApp从ods_base_log读取数据，进行分流
 *              启动 dwd_start_log      曝光 dwd_display_log      页面 dwd_page_log
 *      >UniqueVisitorApp从dwd_page_log读取页面日志，进行去重
 */
public class UniqueVisitorApp {
    public static void main(String[] args) throws Exception {
        //TODO 1.基本环境准备
        //1.1 流处理环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        //1.2 设置并行度
        env.setParallelism(4);

        //TODO 2.检查点相关设置(略)
        //TODO 3.从Kafka中读取数据
        //3.1 声明消费的主题以及消费者组
        String topic ="dwd_page_log";
        String groupId = "unique_visitor_app_group";

        //3.2 创建消费者对象
        FlinkKafkaConsumer<String> kafkaSource = MyKafkaUtil.getKafkaSource(topic, groupId);
        //3.3 消费数据 封装为流
        DataStreamSource<String> kafkaDS = env.addSource(kafkaSource);

        //TODO 4.对流中数据类型进行转换
        SingleOutputStreamOperator<JSONObject> jsonObjDS = kafkaDS.map(JSON::parseObject);

        //jsonObjDS.print(">>>");

        //TODO 5.按照mid对数据进行分组
        KeyedStream<JSONObject, String> keyedDS = jsonObjDS.keyBy(jsonObj -> jsonObj.getJSONObject("common").getString("mid"));

        //TODO 6.过滤
        SingleOutputStreamOperator<JSONObject> filterDS = keyedDS.filter(
            new RichFilterFunction<JSONObject>() {
                private ValueState<String> lastVisitDateState;
                private SimpleDateFormat sdf;

                @Override
                public void open(Configuration parameters) throws Exception {
                    sdf = new SimpleDateFormat("yyyyMMdd");
                    ValueStateDescriptor<String> valueStateDescriptor
                        = new ValueStateDescriptor<String>("lastVisitDateState", String.class);
                    valueStateDescriptor.enableTimeToLive(
                        StateTtlConfig.newBuilder(Time.days(1))
                            //.setUpdateType(StateTtlConfig.UpdateType.OnCreateAndWrite)
                            //.setStateVisibility(StateTtlConfig.StateVisibility.NeverReturnExpired)
                        .build()
                    );
                    lastVisitDateState = getRuntimeContext().getState(valueStateDescriptor);
                }

                @Override
                public boolean filter(JSONObject jsonObj) throws Exception {
                    String lastPageId = jsonObj.getJSONObject("page").getString("last_page_id");
                    if (lastPageId != null && lastPageId.length() > 0) {
                        //如果last_page_id要是不为空   那么说明从其他页面跳过来的  ，直接将这条数据过滤
                        return false;
                    }
                    //---对一天的多次访问进行去重---
                    //获取上次访问日期
                    String lastVisitDate = lastVisitDateState.value();
                    Long ts = jsonObj.getLong("ts");
                    String curVisitDate = sdf.format(ts);
                    if (lastVisitDate != null && lastVisitDate.length() > 0 && curVisitDate.equals(lastVisitDate)) {
                        //已经访问过
                        return false;
                    } else {
                        //还没有访问过
                        lastVisitDateState.update(curVisitDate);
                        return true;
                    }
                }
            }
        );

        filterDS.print(">>>>");

        //TODO 7.将过滤后的数据写到kafka的dwm层
        filterDS
            .map(jsonObj->jsonObj.toJSONString())
            .addSink(MyKafkaUtil.getKafkaSink("dwm_unique_visitor"));

        env.execute();
    }
}
